AI Architect Agentic Generative AI

Benefits:

Oppurtunity for Advancement

Long Term

Competitive salary

AI Architect Agentic & Generative AI Work Type: Full-Time, Onsite Location: Dallas, Texas Interview Mode: In-Person Work Auth : Must be authorized to work in the U.S. Domain: Enterprise AI / Agentic AI / AWS Bedrock Compensation: Competitive, commensurate with experience

As AI Architect – Agentic & Generative AI, you will be responsible for defining, building, and scaling enterprise-grade agentic AI architecture on AWS. This role focuses on establishing frameworks, patterns, and guardrails that enable safe, reliable, and cost-efficient AI solutions, leveraging Amazon Bedrock (Agents, Knowledge Bases, Guardrails, Flows) and Claude models. You will collaborate with cross-functional teams in product, engineering, data, and security to deliver next-generation AI capabilities — including retrieval-augmented generation (RAG), multi-agent orchestration, and governed AI operations — driving measurable business impact through intelligent automation and decision-making systems.

Responsibilities

Define and evolve the enterprise agentic AI architecture, establishing reusable frameworks and standards for RAG, tool/function calling, and multi-agent orchestration.

Design and implement AI solutions using Amazon Bedrock and integrate with core AWS services (Lambda, Step Functions, EventBridge, ECS/EKS, S3, Aurora, OpenSearch, DynamoDB).

Drive adoption of agentic AI patterns — planning, memory, and human-in-the-loop — ensuring alignment with enterprise security and compliance frameworks.

Guide model selection and optimization (Claude family and Bedrock models), including prompt schema design, adapters, and fine-tuning strategies.

Implement advanced RAG pipelines with optimized chunking, reranking, grounding, and hybrid/vector retrieval using OpenSearch and pgvector.

Apply Guardrails and data-governance controls (IAM/ABAC, KMS, private networking) to ensure privacy, PII protection, and compliant operations.

Establish observability and reliability frameworks — including evaluation pipelines, tracing, cost metrics, fallbacks, and A/B testing.

Collaborate with platform and DevOps teams to enable governed AWS landing zones, CI/CD automation, and environment management for AI workloads.

Publish architecture blueprints, starter kits, and best-practice guides for AI engineers and developers.

Mentor engineering teams and contribute to hiring, training, and AI community enablement initiatives.

Research and assess emerging AWS and open-source agentic tools, proposing pragmatic adoption strategies.

Required Skills & Experience

8+ years designing and implementing large-scale distributed or cloud systems (including 4+ years on AWS).

2+ years building AI/ML or generative AI solutions in production environments.

Hands-on experience with Amazon Bedrock (Agents, Knowledge Bases, Guardrails) and Claude models.

Deep understanding of RAG design, hybrid/vector search (OpenSearch, pgvector), grounding, and citation techniques.

Proficiency in Python (preferred) or similar modern programming languages.

Solid grasp of AWS orchestration services (Lambda, Step Functions, EventBridge) and CI/CD practices.

Applied knowledge of AI governance, security, and observability (IAM, KMS, Guardrails, evaluation, tracing).

Excellent communication and architectural documentation skills.

Preferred Qualifications

Expertise in Agentic AI systems, including multi-agent workflows, tool/function calling, and memory architectures.

Experience with LangChain, LangGraph, or similar orchestration frameworks.

Advanced prompt design, RAG optimization, and model customization experience.

AWS Certifications – Solutions Architect (Professional) or Machine Learning Specialty.